activity
20192022
most citedRethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective

44 citations · 55 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20225 cited

Cross-Domain Correlation Distillation for Unsupervised Domain Adaptation in Nighttime Semantic Segmentation

Huan Gao, Jichang Guo, Guoli Wang +1

The performance of nighttime semantic segmentation is restricted by the poor illumination and a lack of pixel-wise annotation, which severely limit its application in autonomous dr…

cs.LG202144 cited

Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective

Helong Zhou, Liangchen Song, Jiajie Chen +4

Knowledge distillation is an effective approach to leverage a well-trained network or an ensemble of them, named as the teacher, to guide the training of a student network. The out…

cs.CV2020

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation

Jialian Wu, Liangchen Song, Tiancai Wang +2

Despite the previous success of object analysis, detecting and segmenting a large number of object categories with a long-tailed data distribution remains a challenging problem and…

cs.CV20196 cited

VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face Recognition

Mengjia Yan, Mengao Zhao, Zining Xu +3

To improve the discriminative and generalization ability of lightweight network for face recognition, we propose an efficient variable group convolutional network called VarGFaceNe…

cs.CV2019

VarGNet: Variable Group Convolutional Neural Network for Efficient Embedded Computing

Qian Zhang, Jianjun Li, Meng Yao +6

In this paper, we propose a novel network design mechanism for efficient embedded computing. Inspired by the limited computing patterns, we propose to fix the number of channels in…